Eugenia Muchnik de RubinsteinDepartment of Agricultural Economics, School of Agriculture,
Catholic University or Chile
Isabel Vial de ValdésInstitute of Nutrition and Food Technology, University or
Chile
Lucía PardoInstitute of Nutrition and Food Technology, University of
Chile

An analysis of national census data since 1907 and long-term
labour trends in the city of Santiago provided background
information for this study to improve the understanding of
current generational differences in women's workforce behaviour.
A life-history methodology, based on data from two age-cohorts
selected from a cross-sectional sample of households, was
implemented to assess the effect of demographic and
socio-economic change and different patterns of family formation
on women's labour-force participation.

Chile is a country with a low population density. The 1970
census gave a total population of 8.9 million, but the National
Planning Office estimated under-enumeration by about 4.8 per
cent, so it was probably in the order of 9.4 million. The last
population census (1982) put the figure at approximately 11.3
million. Since 1970, the annual rate of population growth has
been between 1.5 and 2 per cent, which is below the average both
for Latin America and for countries with similar per capita
incomes. This growth is almost exclusively the result of natural
Increase.

Labour-force participation rates, which express the ratio
between the population in the labour market and the total
population of 12 years of age and over, are influenced by both
demographic and socio-economic change. Three main demographic
trends have shaped population growth in Chile. The first was a
steady decline in mortality rates starting in 1907, which
resulted in greater longevity, especially for women. The second
was a proportionally greater decline in infant mortality rates,
which followed much later. In 1960, Chile had one of the highest
infant mortality rates in Latin America- 120.3 deaths per 1,000
live births. By 1970, the rate had dropped by 34 per cent;
neonatal (less than 28 days) rates had fallen by 11 per cent and
general mortality had decreased by 30 per cent. Between 1970 and
1980, infant mortality was further reduced by 60 per cent, the
neonatal rate by 48 per cent, and general mortality by 23 per
cent. The decline was fastest in the periods 1976-1980 and
1980-1983.

Third, there was a long-term drop in the birth-rate after the
1920s and 1930s, (with the exception of the period 1952-1960),
which became particularly noticeable after 1970. These
demographic characteristics have affected the structure and
composition of both the working and the total population. For
example, the increase in population growth in the 1950s partially
explains the decline in the total labour force in the 1970s and
early 1980s.

These changes have altered both the age distribution of the
population and the proportion of the population in the labour
force. While the total labour force declined during the second
half of the 1960s, it has been increasing since 1970. The
National Bureau of Statistics (INK) estimated it to be
approximately 2.9 million in 1970 and 3.9 million in 1984. An
examination of census data since 1907 shows that male and female
labour-force participation has declined, although both series
present long-term cyclical changes. Since the 1952 census, male
participation has declined comparatively more than female
participation, which the 1982 census shows to have increased
since 1970 (Muchnik and Vial, 1987). Women's workforce
participation in the period 1960 to 1982 was relatively stable,
fluctuating between 20.9 and 26.5 per cent. At the end of 1984,
30.7 per cent (1,196,100) of the workforce were women. By
mid-1985, their proportion had increased to 34.6 per cent, a rise
of 3.9 per cent in one year. In spite of this and the widespread
increase in women's labour-market participation in developing
countries in recent decades, women in Latin America, including
Chile, have had one of the lowest participation rates, although
they have had at least as much, and often more, formal education
and technical training than women in the rest of the third world.

In Chile, as in other Latin American countries, there has been
a significant rural-urban migration, particularly during the
1950s and 1960s. The impact of migration on the participation of
women in the urban labour market is not easy to identify because
it occurred simultaneously with other changes like increased
enrolment in secondary education. The number of girls coming in
to look for work may have been counterbalanced by those who
stayed on in school and so sought employment later, with the
result that the effect on the participation rate was probably
postponed until the 1970s.

Labour-force participation rates are also influenced by
socio-economic factors including education, financial pressures,
and modifications in role perceptions. There have been important
changes in illiteracy rates, school attendance, and the average
educational level in Chile. Illiteracy has decreased
substantially since 1907, while secondary-school attendance has
continued to increase since the educational reform in 1965. Since
1940, the literacy rates of men and women have been about the
same, and no significant gender differences in terms of years of
education are apparent in the 1982 census.

These trends in education affect labour-force participation as
well as the age distribution of the economically active
population. An important proportion of very young people (12 to
14 years of age) began to postpone their participation in the
labour force by extending their schooling; after 1960, there was
an even greater reduction in the proportion of working women in
the 15-19 age-bracket. Increased female participation rates since
1977 could be associated with the higher wages expected to follow
the rise in education levels, which is reflected in the greater
number of women professionals and technicians.

A comparison between 1960 and 1982 census data shows a 25 per
cent increase in the proportion of married women in the labour
force. This is not so much due to a small observed increase in
nuptiality rates, but rather to the higher proportion of married
women who took up formal economic activity. It is also evident
that the labour-force participation of married women with one to
four children increased between 1961) and 1982. It is not yet
clear whether this represents a long-term trend or is more a
consequence of deteriorating economic conditions. Rosales (1979)
suggests that in a recession the labour-force participation of
low-income women increases, while that of medium- and high-income
women decreases. The lower real wages and general unemployment
force poorer women, including those with children, to work in
order to maintain family income. Better-off women, on the other
hand, are deterred from entering the workforce by the lower real
wages and the higher opportunity cost of their time.

This is borne out by data which show that the workforce
participation rates of poorer women increased from 18 to 22.4 per
cent during 1975, a year of crisis characterized by rising and
falling real incomes. The participation of middle- and
high-income women decreased significantly at this time.

Another indicator of their increasing involvement in formal
economic activity and of their need to work in difficult times -
was their participation in government programmes like the
Programa de Empleo Mínimo (PEM) (Minimum Employment Programme)
and, later, in a special programme for heads of households,
Programa de Ocupación para Jefes de Hogar (POJH). Women's high
participation rates in these programmes was remarkable,
especially as many of them had to cope simultaneously with child
care. A survey of 10,000 PEM participants in June 1982 showed
that 52.3 per cent of them were women (Cheyre and Ogrodnic,
1982). Seventy per cent were aged between 18 and 40, and so
likely to be raising children, and 22 per cent were invalids and
sick women who worked up to eight hours a day in the programme.
While there are as yet no comparable studies of the POJH program,
a newspaper survey of eight communities showed that a somewhat
lower proportion of women also took part in this programme, in
which they worked seven hours a day, frequently performing the
same heavy duties as men (Buvinic, 1983).

According to consumer demand theories, individuals and
families seek to maximize the relative benefits that they
perceive that they derive from the consumption of goods, some of
which have to be purchased and some of which are produced at
home, and from leisure time. In order to obtain the market goods,
members of the household must devote part of their time to work
in order to generate income. This in turn implies less time for
either leisure or the production of other goods or services in
the home. This dilemma is particularly relevant in the case of
housewives, as the production of domestic goods and services is
very time-consuming and therefore competes with the allocation of
time to market work. Cultural norms in countries like Chile
usually assign household responsibilities such as child care,
household maintenance, and food production to women.

It is well known that conventional definitions of women's
activities consistently underestimate their economic functions as
well as their productive contribution to society. Several
features of women's work at home contribute to this. The partial
and sporadic nature of women's income-generating activities,
payments in kind, and the fact that many of their tasks (for
example, child care, washing, or sewing) are carried out
concurrently with regular home-keeping duties make it difficult
to observe and measure the full extent of their economic
activities. Sometimes their work is not even perceived as such by
women themselves, and although household activities which do not
generate income also have significant economic value, they are
not usually included in national accounts or statistics.

When an individual does not participate in the labour market,
it is possible to estimate his or her reservation wage, that is,
the maximum wage at which the individual is not willing to work
in the market. In other words, the reservation wage represents
the value assigned to time spent in activities outside the
market. The individual's willingness to participate in the labour
market will depend therefore on the difference between the market
wage and his or her reservation wage. For example, a housewife
may seek employment if the wage she can earn is greater than the
opportunity cost of her time. Because of their greater domestic
responsibilities, Pardo (1983) has postulated that, other things
being equal, the reservation wage for women is significantly
higher than for men and tends to increase with the number of
children.

Women's labour-force participation rate will vary according to
marital status, number of children, and other factors including
education, previous workforce experience and training, health,
nutrition, and, of course, economic pressures and opportunities.
Its duration is not merely a matter of length of employment in
terms of years or hours per week, but also of disruption and
discontinuity. Research into these matters has implications for
the well-being of the women and their households as well as for
the economic development of their country.

Two sources of information were used in this study: an
employment survey of a sample of 1,060 households carried out by
the Institute of Nutrition and Food Technology (INTA) and the
Department of Agricultural Economics of the Catholic University
(DEAUC) in October 1985; and a second survey, also implemented by
INTA/DEAUC, which sought retrospective information on the work
history of a subsample of approximately 1,000 women drawn from
the earlier group and was carried out in April 1986. Both were
carried out under contract with the Department of Economics of
the University of Chile, which conducts periodic employment
surveys in Santiago. Both samples covered households from all
income levels. These surveys were conducted through personal
interviews in the home, and aimed to measure employment rates and
patterns and to reveal changes in these over time. Generally
speaking, employment behaviour was considered within a reference
period of one week. However, questions on the previous month and
the previous year were also included in order to cover partial
and sporadic economic activities.

The primary aim of the second survey, in April 1986, was to
gather information on paid work and other events in each woman's
life since she entered the formal educational system. As the
study sought to observe change through time, two age-cohorts were
defined: one of women between 15 and 32 and the other of those
between 39 and 65. The data on the work history of each woman is
continuous, with information on events at selected points in
their lives. The respondents were asked about the sequence of
their working activities between starting school and the time of
the survey. They were requested to recall each job and to
describe it, specifying the month and year in which they began,
its duration, and the reasons for leaving. The same methodology
was used to obtain data on other aspects of their lives -
education, marital history, fertility and the use of
family-planning methods - which could build up a more complete
description of the main socio-economic factors which influence,
and are influenced by, women's participation in the labour force.

The pattern of each of these life events is set out in
frequency tables compiled on the basis of the woman's age at the
time the events took place rather than the calendar year. The
results are presented by age-cohort and by income group. The
latter are designated low, medium, and high (strata 1, 2 and 3
respectively), with each level corresponding to one-third of the
initial sample of 3,060 households classified according to per
capita family income. However, the proportion of each cohort in
the three income levels in the subsample of 1,000 households is
not exactly one-third: women in cohort 1 are evenly distributed
among the three income groups, but a slightly higher percentage
of the women in cohort 2 belong to the lowest income group.

The study showed that 51 .8 per cent of the economically
active population in the sample were actually in the labour
force; the participation rates were 70.1 per cent for men and
36.6 per cent for women. The male unemployment rate was higher
(14 per cent) than the female rate (9.9 per cent).

A breakdown of the reported working population by economic
sector showed the female workforce to be heavily involved in the
service sector: 59 per cent of them were employed there as
compared to 34 per cent of the male workforce. Women worked
mainly in personal services (29.7 per cent), followed by
manufacturing (17.5 per cent), commercial (16.8 per cent), and
government services (11.2 per cent). A very small percentage of
them worked in agriculture and fisheries (1.9 per cent) and in
housing construction (1 per cent).

Figures for the distribution of the labour force by occupation
indicated that approximately 38 per cent of women were
white-collar workers, around 27 per cent were in domestic
service, 15.5 per cent were self-employed, and 13 per cent were
blue-collar workers. About 5 per cent worked in one of the
government-subsidized employment programmes (PEM and POJH). Less
than 5 per cent were employers. The number of women in domestic
service stood out: 485 out of 2,930 working women in the sample,
or one woman in less than every four, worked as housemaids. It is
interesting that none of the female heads of household was so
employed.

Eighty-nine per cent of the women worked for wages or income
for 25 to 58 hours per week. Those who had permanent jobs and
related social security coverage had slightly longer average
working hours than other female workers; however, the women
participating in one of the subsidized employment programmes, PEM
or POJH, worked only about 25 hours per week.

Figure 1 shows the frequency of women's participation in the
labour force by cohort: in other words, it shows the number of
women who worked or sought a job at each age. Obviously, the
frequency curves of the younger cohort are, by definition,
truncated at 32 years of age, or at 29 if the number of
observations above that age was too low to be representative. Nor
was it feasible to estimate averages for the younger cohort as
the relevant events had not yet been completed in most cases.

According to figure 1, a higher proportion of the older cohort
was working when they were 20 or less, but the opposite is true
after the age of 21. In the older cohort, the percentage of women
in the labour force increased with age up to 49 per cent at 24
years, then declined by about 10 per cent between 24 and 27, and
continued to do so very slowly thereafter. The participation of
the younger cohort increased constantly up to the cut-off point
at 29, when there was around 57 per cent. Only 42 per cent of the
older cohort were working at this age. Although the younger
cohort postponed entry into the labour force by an average of
five years, its rate of participation was substantially above
that of the older group.

Within cohort 1, the pattern of labour-force participation
differs substantially according to income group (fig. 2). Women
in the low-income group exhibit significantly higher frequencies
of participation when they are younger than either the medium- or
high-income women. However, from around 26 onwards, and
particularly after 39, their labour-force participation drops. On
the other hand, the participation of the high-income group
increases with age up to 29, where it stabilizes at approximately
45 per cent till 46, when it begins to increase again, reaching a
peak of around 56 per cent in the early fifties. The
middle-income group presents the classic double-peak pattern of
labour-force participation, in which women work before or during
their childbearing years, leave the labour force to raise their
children, and subsequently return to work.

Fig.
1. Women in the labour force at each age

Fig.
2. Cohort 1: Women in the labour force at each age by income
group

Fig.
3. Cohort 2: Women in the labour force at each age by income
group

Figure 3 shows that in the younger cohort the labour-force
participation of the low-income group is generally not above that
of the other two income strata. It increases up to 22 years and
is maintained at an average rate of 43 per cent up to 29. The
pattern of labour-force participation in the high-income group is
similar to that in the older cohort, in that it increases with
age, but the participation rates after 21 years are much higher,
reaching 78 per cent at 29, compared to only 47 per cent of this
segment of the older cohort at the same age.

The separate and joint impact of demographic, socio-economic,
and behavioural variables on the women's labour-force
participation was assessed by means of multivariate regression
analysis. Econometric analysis of the survey data focused on the
main factors that determine women's wages and the way in which
wages and other factors like education and family formation
influence women's decisions about employment.

A comparison of working behaviour by income strata independent
of age shows that the impact of changes in wage rates was much
more significant in the middle than in either the high- or
low-income groups. Married women in the medium- and high-income
groups spent fewer hours in formal work than single women, but
marital status was not a significant determinant of low-income
women's working behaviour. For women in the high-income group,
the availability of domestic staff increased the probability of
market work. The analysis shows that, in the lower socio-economic
group, an increase in family income induced women to work fewer
hours. This also occurred in the high socioeconomic group, but to
a much smaller extent. On the other hand, increases in family
income had a positive effect on women's employment in the
middle-income stratum.

Real wage levels were shown to be an important factor in
women's decision to enter the labour force and also in the number
of hours worked per month. The positive impact of wage rates on
hours of work and on the probability of working was stronger in
the younger cohort. This, in combination with higher educational
levels, was having a substantial effect on the labour-market time
allocation of younger women.

Education

Educational attainment was a major determinant of average
earnings. The higher the level of school completed, the higher
the wage which could be expected. The hourly income of women who
had only completed primary school was not much better than that
of those who were illiterate. However, secondary education or
incomplete tertiary studies led to double the income of those who
had only primary schooling, and those with a university degree
earned four times as much. Women with technical training earned
somewhat less than those who had secondary school qualifications.
The impact of education on female earnings was greater in the
younger cohort. Of course, age and working experience have a
considerable influence on hourly earnings, but this cannot be
considered so important in the younger cohort because of the
early cut-off point.

The educational system in Chile is in four parts, primary
(eight years), secondary (four years), technical (from one to
three years) and university (five to seven years). In 1965,
secondary education was reduced to four years, and primary
schooling expanded from six to eight years, so that free
compulsory education could be extended by two years. The data for
the older cohort in this study have been adjusted so that valid
comparisons between the cohorts can be made.

Important differences between them can be observed in the
proportion of each completing primary education. The cumulative
frequency distribution indicates that about 29 per cent of the
older cohort had finished their primary education at 13, compared
to 39 per cent of the younger cohort. About 53 per cent of cohort
1 had finished primary education by 16, compared to 76 per cent
of cohort 2. This difference of approximately 23 per cent in
favour of the younger generation remains unchanged thereafter.

Looking at the differences between income groups, a greater
proportion of the high-income group completed their primary
education in both cohorts, as might be expected, but this
difference between the income groups decreased drastically within
the younger cohort. The proportion of low- and medium-income
groups finishing primary education by 13 increased from 12 to 29
per cent and from 15 to 34 per cent respectively between cohorts
1 and 2. This means that better access had more than doubled the
proportion of low- and medium-income women completing primary
education.

Turning to secondary education, the highest frequencies of
completion among the older cohort occur at 17 and 18, while they
are concentrated at 17 for the younger cohort. The cumulative
profiles show that by 19, 39 per cent of the women in cohort 2
had finished secondary education, compared to only 19 per cent of
cohort 1. The observed difference remains unchanged thereafter.
In other words, the proportion of women who completed secondary
education has also doubled among the younger group.

The probability of completing secondary education is much more
restricted at the lower income levels in both cohorts, in spite
of the narrowing differences between them in cohort 2. Among
cohort 1, only 1.7 per cent of the low-income women had completed
secondary education at 17, while in cohort 2 the proportion
increased to 10 per cent. In the medium-income groups, the
proportion increased from 2.3 to 15 per cent. The percentage of
women who had completed secondary education at 17 also increased
- from 15 to 34 per cent - in the high-income group. The data
indicate not only improved access to secondary education but,
even more important, a better rate of completing it.

The figures for female enrolment in higher education are much
lower. Within the older group, the highest frequencies of women
graduating from university occur at ages 22 and 24. In the case
of cohort 2, this is at 22. Only 4.5 per cent of women in cohort
I had finished university studies at 24. The proportion had
increased to 7 per cent in the second cohort, a figure which may
rise as some of the younger women were still university students
at the time of the survey.

Looking at variation by income level within the two cohorts,
none of the low-income women in the sample had graduated. Four
women from this group in cohort 2 did enter university, but none
had finished: they were either still studying at the time of the
survey or had dropped out. Within the older cohort, the majority
of high-income women graduated from university at 22, while women
of the medium-income level did so two years later at 24. In
cohort 2, the same difference between the income groups in age at
graduation is maintained, but graduation rates increased. Most
women graduates come from the higher-income strata. Comparing
educational levels by gender suggested the greater socioeconomic
vulnerability of households which were headed by women.
Six-and-a-half per cent of these women were illiterate, compared
to only 1.9 per cent of male heads of households. Logically, this
unfortunate disparity continued as educational levels rose: 30
per cent of female heads of households had completed secondary
schooling, compared to 35.4 per cent of the men, and the
proportion of women in this position with a university education
(8.8 per cent) was only about half that of men (16.3 per cent).

Fig.
4. Age at first marital union by cohort

Marriage

Figure 4 indicates that women in first cohort married younger
than those in cohort 2, although both frequency curves exhibit a
similar shape. Two peaks are observed in cohort 1, at ages 19 and
21; within cohort 2, most married in their early twenties.

Within the older group, patterns vary according to income
levels (fig. 5). A higher proportion of the women in the medium-
and low-income groups married younger (before 19) than those in
the higher-income stratum, with a fairly constant difference of
about five percentage points. The highest frequency of marriage
occurs at 19 among women of medium- and low-income groups, but at
27 for the high-income group. A second but lower peak is observed
at 21 for low-income women, at 23 for medium-income women, and at
21 for those in the high-income group.

Fig.
5. Cohort 1: Age at first marital union by income group

Fig.
6. Cohort 2: Age at first marital union by income group

Analysing income groups within cohort 2 shows that a
relatively higher percentage of low-income women marry before 21,
as do a lesser proportion of the medium-income group The lowest
incidence of marriage before age 21 is among the high-income
group (fig. 6). The highest frequencies of first marriage occur
at 21, 23, and 24 for the low-, medium-, and high-income groups
respectively. The pattern in figure 6 reveals a clear decline
from the older to the younger cohort in the proportion of women
married at similar ages. Most (approximately 85 per cent) of the
older cohort were already married at 30, compared to 64 per cent
of the women in cohort 2. This lower nuptiality rate among the
younger women appears to contradict the slight increase observed
in the census data.

Contraception and Fertility

The women were asked about the age they began using
contraception and their pattern of subsequent usage. The
frequencies of first usage in both cohorts are shown in figure 7.
Contraception was initiated earlier in the younger cohort. It is
also clear from the data that, at least tip to 26, the younger
women were much more likely to practice family planning, with a
particularly rapid comparative increase in usage between 16 and
20. The peak frequencies are at 22 for the younger cohort and at
27 and 30 for cohort 1.

Figure 8 illustrates the proportions of women in cohorts and 2
practicing family planning at each age. Again, the higher
proportion of younger women using contraceptive methods is
evident: at 31, the last age at which the cohorts can be validly
compared, about 45 per cent of the older cohort were practicing
contraception, compared to 64 per cent of the younger group.

The difference in usage between income groups within cohort 1
can be observed in figure 9. It is minimal up to 30 years of age.
Subsequently, the highest frequency in the low-income group
occurs at age 33, while the peak occurs at 40 for both the
medium- and high-income groups. Within the younger cohort, figure
10 shows that the use of contraceptives is highest in the
low-income group, followed by the medium- and then the
high-income group. For example, at age 22, 58 per cent of the
low-income women were using contraceptives, compared to 28 and 20
per cent in the middle- and high-income segments respectively.
The corresponding figures for the older cohort were considerably
lower- 13 and 11 per cent. Wide access to family-planning
programmes is reflected in the fact that there are no particular
differences between the income strata apparent within cohort 1,
and the lowest income group in the younger cohort includes the
highest proportion of women using contraceptives at 29 or
younger.

Fig.
7. Age at first use of contraceptive method

Fig.
8. Use of contraceptive methods at each age

Fig.
9. Cohort 1 Use of contraceptive methods at each age by income
group

Fig.
10. Cohort 2: Use of contraceptive methods at each age by income
group

Figures 11 to 20 show the frequencies of events related
pregnancy according to age cohort and income level. Figure 11
depicts the distribution of women by age at the end of first
pregnancy, showing the proportion of the total number of women in
the respective cohorts becoming pregnant for the first time at
each age. It should be remembered that in the younger cohort all
first pregnancies may not necessarily have occurred by age 29. No
clear differences between the cohorts are apparent in the shape
of the frequency curve, although the curve for the younger cohort
is usually below that of the older cohort.

This becomes clearer in figure 12, which gives the cumulated
frequencies by cohort and shows that, from the age of 15, the
proportion of first pregnancies occurring is lower among the
younger women, with a difference between the cohorts which
increases with age. Only about 64 per cent of the younger cohort
had been pregnant by the time they were 29, compared to
approximately 79 per cent of the older cohort.

A different pattern appears when differentiating by income
level (figs. 13 and 14). In cohort 1, the older group,
approximately 3 per cent of the women in the lower-income group
had completed their first pregnancy at 15, and, up to 19, they
had experienced a higher accumulated proportion of pregnancy
events than those in the other two income groups. Those in the
higher income stratum postponed their first pregnancies still
later than the others, with the highest frequencies occurring
between 22 and 28.

Within the younger cohort, there is a much more marked
difference between the income groups, as shown in figure 14. The
pattern of the low-income group shows that their first
pregnancies occur at significantly younger ages, while the
opposite is observed in the high-income stratum. The latter
reaches a peak frequency at 26, compared to 20 in the low-income
group. The peak for the middle-income group is at 24. Although it
is not shown in the figure, first pregnancies begin at 13 in the
low-income group, but not till after 15 in the middle-income
stratum.

Data on second pregnancies are presented in figures 15 to 17.
Figure 15 shows a higher proportion of second pregnancies at
lower ages among the older cohort. These differences within the
cohort are less evident when disaggregated by income level,
although in the younger cohort considerably more of the poorer
women had second pregnancies at lower ages (figs. 16 and 17).

Figures 18 to 20 refer to the frequency of pregnancy by age
and cohort, independent of the number of pregnancies for each
woman. It can be seen in figure 18 that the frequency curve of
the older cohort is much higher than of the younger cohort. For
example, at 22 about 11 per cent of the younger women were
pregnant, compared to about 25 per cent of the older cohort. A
similar difference is observed at later ages.

Looking at pregnancy and income level in both cohorts figs. 19
and 20), it may be seen that a higher proportion of women in the
lower-income group were pregnant at each age. The difference in
frequency between the low- and the high-income groups is
particularly striking between ages 19 and 25 in cohort 1 and
between ages 18 and 20 in the younger cohort. In the high-income
stratum of cohort 2, the peak frequency occurs at ages 21 and 25
(11 per cent of the in each case), compared to 27 (20 per cent of
the stratum) in the middle-income group and 19 (21 per cent of
the relevant sample) in the low-income group.

Women's working behaviour in urban Chile varies markedly
according to socioeconomic background, age, education, and the
process of family formation. The data give a clear picture of
many aspects of the female workforce, and, of particular
importance to the country's human resource development, it
delineates many of the factors that influence women's
participation in it. It shows that younger women now postpone
entry into the labour force. The life-histories of both cohorts
indicate that, on average, the older group started working five
years earlier than the younger group; however, the labour-force
participation of the latter increased from 21 years of age on,
although, as their participation curve is censored by their
youth, it is not possible to draw any conclusions about their
working patterns after the age of 29. In the older cohort,
participation rates started declining at 23. Analysis by income
groups reveals higher workforce participation among low-income
women up to approximately 30 in the older cohort. After 35,
labour-force participation among the low- and medium-income
groups within this cohort decreases, but the opposite trend
characterizes the high-income group. Within cohort 2 there is no
difference in working behaviour according to income level up to
20. From there on, the women who arc better off show a
substantially higher rate of participation, as in the older
cohort.

The differences described are the result of a number of
factors, one of the most important being changes over time in
education. A higher percentage of women in the younger cohort had
completed primary education. The proportion of women who finished
primary education in both cohorts increased as income rose.

The difference in the higher proportion of the younger women
completing secondary education is even greater than it is for
primary schooling. Moreover, the gap between the socio-economic
groups in terms of secondary education is narrower within the
younger cohort. Only a few of the older women from the medium-
and low-income groups stayed in the educational system until they
had completed secondary schooling. Finally, it is clear that
higher income has been closely associated with access to higher
education in both cohorts. None of the low-income women in the
sample had completed university-level education.

The data support the hypothesis that women are postponing
entry into employment while they acquire better educational
qualifications. As a result of these higher attainments, they can
expect better wages, which in turn encourages them to join the
workforce.

Family formation is also an important factor in participation.
By the age of 30 approximately 64 per cent of the women in the
younger cohort had married, compared to 85 per cent of those in
the older cohort, which indicates a lower rate of nuptiality
within the younger group. Consistent with this, age at first
marriage has been delayed by an average of three years in the
younger cohort. This postponement is longer among the high-income
women within the cohort, so that their peak age at marriage is
24, compared to 19 for the poorest group.

The cumulative frequency of women pregnant for the first time
at each age shows that fertility is lower among the younger women
who use contraceptive methods sooner and more extensively. At 29,
almost 63 per cent of them were practising contraception,
compared to 38 per cent of the older cohort at the same age.
Pregnancy occurs earlier among the low-income group in both
cohorts. The frequency of second pregnancy at each age is also
lower for the younger cohort, at least until the cut-off age at
29. Within this cohort, the second pregnancy takes place much
earlier in the low-income group, with a peak at ages 21-22,
compared to 28 for the medium- and high-income groups. Comparing
the proportion of women who were pregnant at each age, whether it
was their first, second, or subsequent pregnancy, shows that the
proportion of women pregnant at 29 or less is approximately 50
per cent lower in the younger cohort, particularly in the
high-income group.

Other trends identified in the survey suggest that while the
number of hours worked per month tended to decrease with age in
the older cohort, the opposite was true in the younger group.
Married women have lower labour-force participation rates than
single women, and those who were employed were likely to work
considerably fewer hours than their single counterparts.

The availability of domestic help or others to provide
substitute child care allowed mothers in both cohorts to increase
their number of hours in the workforce considerably. Other things
being equal, increased family income (apart from women's
earnings) led to a reduction in formal work in the older cohort,
suggesting that, at higher income levels, women allocate more
time to domestic duties or leisure. Family income did not seem to
influence working decisions in the younger cohort. Head of
household status appeared to limit women's work in cohort 1,
another indication of the competing demands on women's time.

Data from employment surveys in Santiago have been showing
changes in the age structure of the female workforce. The
life-history approach of the present study has made it possible
to link these trends to behavioural differences between
age-groups that have been induced by various socio-demographic
changes. Information provided by life-history methodology has
allowed more precise identification of the sequence and
relationships of events and their impact on the structural
changes observed in female labour-force participation.

The distinction made in the analysis between income strata was
extremely useful in understanding important differences and
patterns within each age-cohort. In certain areas, such as
education, marriage, and age at first pregnancy, the differences
between income groups within the age-cohorts were more striking
than those between the two cohorts.

It is clear that the policies to increase access to education
and family planning introduced since the mid-1960s have borne
fruit. The data show that younger women tend to have much more
education, to delay marriage and childbearing, and to have lower
fertility rates than their older counterparts. In fact, the
changes observed in the family formation process are similar to
those described in developed countries.

Thus, an indirect result of these policies has been to enhance
the ability and desire of women to participate in formal economic
activity, and future policies must take their economic needs,
workforce potential, and personal aspirations into account.